Managing checkpoint queues in a multiple node system

ABSTRACT

Techniques are provided for managing caches in a system with multiple caches that may contain different copies of the same data item. Specifically, techniques are provided for coordinating the write-to-disk operations performed on such data items to ensure that older versions of the data item are not written over newer versions, and to reduce the amount of processing required to recover after a failure. Various approaches are provided in which a master is used to coordinate with the multiple caches to cause a data item to be written to persistent storage. Techniques are also provided for managing checkpoints associated with the caches, where the checkpoints are used to determine the position at which to begin processing recovery logs in the event of a failure.

RELATED APPLICATIONS AND CLAIM OF PRIORITY

This patent application is a divisional application of and claimspriority to U.S. patent application Ser. No. 10/092,047, filed Mar. 4,2002, now U.S. Pat. No. 7,065,540 entitled MANAGING CHECKPOINT QUEUES INA MULTIPLE NODE SYSTEM, the contents of which is hereby incorporated byreference as if fully set forth herein under 35 U.S.C. §120, which is acontinuation-in-part and claims priority to U.S. patent application Ser.No. 09/199,120, filed Nov. 24, 1998, now U.S. Pat. No. 6,353,836entitled METHOD AND APPARATUS FOR TRANSFERRING DATA FROM THE CACHE OFONE NODE TO THE CACHE OF ANOTHER NODE, the contents of which is herebyincorporated by reference in their entirety.

This patent application is also related to and claims priority from U.S.Provisional Patent Application No. 60/274,270, filed Mar. 7, 2001,entitled METHODS TO PERFORM DISK WRITES IN A DISTRIBUTED SHARED DISKSYSTEM NEEDING CONSISTENCY ACROSS FAILURES, the content of which ishereby incorporated by reference in its entirety.

This patent application is also related to U.S. patent application Ser.No. 10/091,618, filed Mar. 4, 2002, entitled METHODS TO PERFORM DISKWRITES IN A DISTRIBUTED SHARED DISK SYSTEM NEEDING CONSISTENCY ACROSSFAILURES, the content of which is hereby incorporated by reference inits entirety.

FIELD OF THE INVENTION

The present invention relates to performing disk writes and, moreparticularly, to coordinating the writing of dirty data items in systemsthat allow dirty versions of a data item to reside in the caches ofmultiple nodes.

BACKGROUND OF THE INVENTION

One way to improve scalability in database systems is to allow multiplenodes to concurrently read and modify data in shared storage. Each nodehas a cache to hold data in volatile main memory and is backed up bynon-volatile shared disk storage. A global lock manager (GLM) or adistributed lock manager (DLM) is used to maintain cache coherencybetween nodes. To provide recovery from node failures that erase thecontents of main memory, the popular Write-Ahead-Logging (WAL) protocolis used. For performance reasons, each node has a private redo log inwhich changes are recorded. To reduce the amount of changes in the redolog that need to be scanned after a node failure, incremental orperiodic checkpoints are typically taken that guarantee that all changesin a data item prior to the checkpoint need not be reapplied to the dataitem in non-volatile storage.

Concurrency Control

Concurrency control between transactions running either on the same nodeor different nodes is implemented through global transactionalpage-level locks or row-level locks. The transaction system can useeither the force policy, where the data items (such as pages/blocks)modified by the transaction are written to stable storage duringtransaction commit, or use the no-force policy where only thetransactions' changes in the redo log are forced at transaction commit.Use of the force policy with page level locks implies that the blocksare modified only by one node (in fact, only by one transaction) and canbe dirtied in only one system's cache at any point. In all othercombinations (i.e. row-level locks with force policy, page-level lockswith no-force, and row-level locks with no-force) the data items can bemodified in multiple systems and a cache coherency mechanism is needed.

The most general case is row-level locks with the no-force data itemmanagement policy. For the purpose of explanation, the examples givenhereafter will be given in the context of systems that use row-levellocks with the no-force data item management policy. However, thetechniques described herein are not limited to that context.

Checkpoint Queues

When a transaction commits, data that reflects the changes made by thetransaction must be stored on persistent storage. In some systems, redorecords that indicate the changes made by a transaction have to bepersistently stored at commit time, but the actual writing of themodified data items themselves can be delayed. A data item that (1)contains changes, and (2) has not yet been persistently stored, isreferred to as a “dirty data item”. In general, the more dirty dataitems that reside in a node, the longer the recovery time will be if thenode fails. Therefore, to ensure that the recovery time is notunacceptably long, a node may maintain a checkpoint queue.

Checkpoint queues contain entries that identify dirty data items. Theentries in the queue are ordered based on the order of correspondingredo records in a persistently stored redo log. In the event of afailure, the redo log must be processed starting with the redo recordthat corresponds to the entry that was at the head of the checkpointqueue.

When a dirty data item is written to persistent storage, the entry forthat data item is removed from the checkpoint queue. When the entry thatis at the head of the checkpoint queue is removed from the checkpointqueue, the point within the redo log at which recovery processing mustbegin changes, resulting in an “advance” of the checkpoint. The furtherthe checkpoint has advanced in the redo log at the time of a failure,the less work has to be done to recover from the failure. Consequently,nodes typically attempt to write to persistent storage the dirty dataitems identified by the entries at the head of their checkpoint queue.However, as shall be described in greater detail hereafter, coordinatingthe writing of dirty data items is particularly important when it ispossible for dirty versions of the same data item to reside in thecaches of multiple nodes.

Transfer of Data Items Through Shared Persistent Storage

When data items can be modified concurrently by multiple systems, amechanism is needed to coordinate the writing of the modified data itemsto stable shared persistent storage. In some systems, this problem issimplified by using the stable shared persistent storage as the mediumfor transferring the modified data items from one node to another. Whena data item that is dirty in a node is needed for modification in adifferent node, the data item is first written to the shared persistentstorage before granting the page lock to the node that wants to modifythe dirtied data item. The same write-to-persistent storage andread-from-persistent storage sequence is used when a different nodeneeds to read the current version of the modified data item.

Transfer of Data Items Through Inter-Connect

In systems that use nonvolatile storage as the medium through which theytransfer data items between nodes, it is not necessary to coordinate thewriting of dirty data items among the different nodes. Each node can usethe conventional mechanism for writing out dirty data items andperforming checkpoints.

In some systems, the modified data item is sent to the requesting nodewithout writing the data item to the persistent storage when therequesting node only needs a consistent snapshot version of the modifieddata item. Hence, with these coherency control mechanisms, althoughmultiple transactions in different nodes can modify the same data itemusing row-level locks before transaction commit, any database data itemis dirty in only one node's cache. Consequently, when a node fails, onlythat node's redo logs need to be scanned from the checkpoint record inthat node to the end of its redo log to recover the database. Further,when multiple nodes fail, each node's redo logs can be scanned andapplied in sequence to recover the database, i.e. there is no need formerging changes from multiple redo logs.

However, to improve data item transfer latency, from a node that has anexclusive lock and that has potentially modified the data item, to anode that requests the same data item for exclusive use or a currentversion for read, it is desirable to directly transfer the data itemfrom the main memory of one node to the main memory of another withoutfirst writing the data item to persistent storage. When a dirty dataitem is transferred from one node to another, a copy of the data item,known as a past image (PI) may or may not be retained in the sendingnode.

When nodes are allowed to transfer dirty data items without storing themto persistent storage, the writing of the dirty data items must becoordinated between the various nodes. If no coordination occurs, a nodethat has transferred a dirty data item may desire to advance itscheckpoint by writing the dirty data item to persistent storage.However, if some other node has already written a more recent version ofthe data item to persistent storage, then writing the dirty data item topersistent storage may corrupt the integrity of the data.

In addition, checkpoints cannot be advanced unless dirty data items arewritten to disk. If a node does not retain dirty versions of data itemsthat the node sends to other nodes, then the node must somehowcoordinate write-to-disk operations with the other nodes.

Further, for a system to be scalable, the number of write-to-diskoperations performed by the system should not be a function of thenumber of nodes in the system. Rather, the number of write-to-diskoperations should simply reflect the number of changes actually made todata items within the system.

Based on the foregoing, it is clearly desirable to provide techniquesfor coordinating the writes of dirty data items in systems in which itis possible for dirty versions of the same data item to reside in morethan one volatile memory.

SUMMARY OF THE INVENTION

Techniques are provided for managing caches in a system with multiplecaches that may contain different copies of the same data item.Specifically, techniques are provided for coordinating the write-to-diskoperations performed on such data items to ensure that older versions ofthe data item are not written over newer versions, and to reduce theamount of processing required to recover after a failure. Variousapproaches are provided in which a master is used to coordinate with themultiple caches to cause a data item to be written to persistentstorage. Such approaches include, but are not limited to, direct writeapproaches, indirect write approaches, owner-based approaches, androle-based approaches. Techniques are also provided for managingcheckpoints associated with the caches, where the checkpoints are usedto determine the position at which to begin processing recovery logs inthe event of a failure.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example, and not by wayof limitation, in the figures of the accompanying drawings and in whichlike reference numerals refer to similar elements and in which:

FIG. 1 is a block diagram illustrating how write-do-disk operations arecoordinated in a direct write approach according to an embodiment of theinvention;

FIG. 2 is a block diagram illustrating how write-do-disk operations arecoordinated in an indirect write approach according to an embodiment ofthe invention;

FIG. 3 a is a block diagram illustrating how write-do-disk operationsare coordinated in an owner-based write approach when the global dirtyflag is false, according to an embodiment of the invention;

FIG. 3 b is a block diagram illustrating how write-do-disk operationsare coordinated in an owner-based write approach when the global dirtyflag is true, according to an embodiment of the invention;

FIG. 3 c is a block diagram illustrating how write-do-disk operationsare coordinated in an owner-based write approach when the write requestis not from the owner, according to an embodiment of the invention;

FIG. 4 a is a block diagram illustrating how write-do-disk operationsare coordinated in a role-based write approach when the mode is local,according to an embodiment of the invention;

FIG. 4 b is a block diagram illustrating how write-do-disk operationsare coordinated in a role-based write approach when the mode is global,according to an embodiment of the invention;

FIG. 4 c is a block diagram illustrating how write-do-disk operationsare coordinated in a role-based write approach when the request is notfrom the exclusive lock holder, according to an embodiment of theinvention;

FIG. 4 d is a block diagram illustrating how write-do-disk operationsare coordinated in a role-based write approach when a transfer isperformed during a write operation, according to an embodiment of theinvention;

FIG. 5 is a block diagram illustrating a checkpoint queue;

FIG. 6 is a block diagram illustrating a checkpoint queue;

FIG. 7 is a block diagram illustrating a checkpoint queue with mergedentries;

FIG. 8 is a block diagram illustrating a checkpoint queue where theentries are batched into bins; and

FIG. 9 is a block diagram illustrating a computer system on whichembodiments of the invention may be implemented.

DETAILED DESCRIPTION OF THE INVENTION

A method and apparatus for coordinating the writing of dirty data itemsis described. In the following description, for the purposes ofexplanation, numerous specific details are set forth in order to providea thorough understanding of the present invention. It will be apparent,however, that the present invention may be practiced without thesespecific details. In other instances, well-known structures and devicesare shown in block diagram form in order to avoid unnecessarilyobscuring the present invention.

Optimizing Systems that Use a Persistent Storage as Medium for Transfer

In systems that use a persistent storage as the medium for transferringdata items between nodes, the latency of transferring a data item fromone node to another may be reduced by modifying the database cachewriting subsystem to give higher priority to writing data items thatother nodes are waiting to read or write. This can be accomplished byhaving a separate queue (a “ping queue”) for dirty data items that needto be written because other nodes are waiting to read or modify them.The dirty data items can be moved to the ping queue on demand when alock manager (which may be either a distributed lock manager DLM or aglobal lock manager GLM) sends a message to the holding node asking forthe holding node to release its lock on the data item.

According to another approach, the latency of transferring a data itemfrom one node to another may be reduced by maintaining a “forced-write”count in each data item header or data item control block. Theforced-write count is incremented whenever a write is performed in orderto transfer a data item to another node. The persistent storage writingsubsystem maintains a high priority queue of dirty data items whoseforced-write count is higher than a certain threshold. Such a queue isused to allow those data items to be written more frequently than otherdirty data items that are not frequently shared between nodes. Inaddition, the latency of lock transfer between nodes is improved becausethe database cache writing subsystem has eagerly written out dirty dataitems in anticipation that the locks on these data items need to bereleased.

However, even when optimized in this manner, systems that use a sharedpersistent storage as the medium for transferring data items betweennodes suffer the overhead associated with writing the data items topersistent storage. The techniques described hereafter relate to systemsin which data items, including dirty data items, can be transferredbetween nodes without first being written to persistent storage.

Correctness and Scalability

In systems that allow dirty data items to be transferred between cacheswithout first being stored on persistent storage, there is a need tocoordinate the writes of the dirty data items in the different per-nodecaches for the sake of correctness as well as scalability. Correctnessrequires that when a node completes a checkpoint (i.e. records astarting point from which changes may need to be applied from its redolog after a failure), a version of every data item that contains changesthat were committed prior to the checkpoint has been written to thenon-volatile persistent storage storage. Further, two nodes must not beallowed to write a data item to persistent storage at the same time(since they may clobber each other's changes) and a node must not beallowed to write an older version of a data item over a more recentversion.

Scalability requires that a persistent storage write of a data itemcovers as many changes as possible even if the changes were made bydifferent nodes. For availability reasons, a database system may wish tolimit the amount of redo log that needs to be scanned and possiblyreapplied after node failure. Hence, the number of database writes couldbe proportional to the number of changes made to data items, but shouldnot be proportional to the number of nodes that are making thesechanges.

Functional Overview

Various techniques are provided for coordinating the writing of dirtydata items to persistent storage in systems that allow a dirty versionof the same data item to reside in multiple caches. According to onetechnique, the coordination is performed using a master assigned to thedata item. According to one embodiment, the master used to coordinatethe writing of dirty versions of the data item is the same entity thatis assigned to manage the locks that govern access to the data item. Insuch an embodiment, the master would typically be a component of a lockmanagement system, such as a lock manager that belongs to either adistributed or global lock management system.

In one embodiment, a node that desires to write a dirty data item topersistent storage sends a persistent storage-write request to themaster assigned to the data item. The master may (1) grant therequesting node permission to perform the write, or (2) inform therequesting node that another node has already written to persistentstorage a version that is at least as recent as the dirty version storedin the requesting node.

In another embodiment, the master may also respond by sending a“write-perform” message to ask a node other than the requesting node towrite to persistent storage a version of the data item that is at leastas recent as the dirty version stored in the requesting node. After theother node sends to the master a “write-confirm” message that the writehas been performed, the master sends a “write-notification” message toinform the requesting node that another node has already written topersistent storage a version of the data item that is at least as recentas the dirty version stored in the requesting node.

Once a particular version of a data item has been written to persistentstorage, the dirty versions of the data item that are the same as orolder than that particular version are “covered” by the writing of theparticular version. Covered versions of a data item no longer need to be(and should not be) written to persistent storage. The nodes thatcontain covered versions are referred to herein as the “interested”nodes.

In addition to informing the requesting node that a data item has beenwritten to persistent storage, the master may send write-notificationmessages to inform all of the interested nodes that the data item waswritten to persistent storage. The write-notification messages to theother interested nodes may be sent immediately upon receivingconfirmation that the data item was written to persistent storage, ordelayed until some other event.

In another embodiment, to avoid the need for every node to ask themaster every time the node wants a dirty data item to be written topersistent storage, the master may grant to a node “ownershippermission” for the data item. While a node holds the ownershippermission for the data item, the node is free to write the data item topersistent storage without sending a write-request message to the masterof the data item. The ownership permission may be granted implicitlywith ownership of the exclusive lock, or it may be granted separatelyfrom and independent of the grant of an exclusive lock.

According to one embodiment, a “global dirty” flag is maintained for adata item. The global dirty flag is set to TRUE if a node transfers adirty version of the data item to another node. If the global dirty flagis set to TRUE when an owner writes a data item to persistent storage,then the owner sends a write-confirm message to the master. The mastermay then send write-notification messages to the interested nodes. Onthe other hand, if the global dirty flag is set to FALSE, then the ownerneed not send a write-confirm message to the master when the ownerwrites the data item.

Direct Write Approach

According to the direct write approach, the writing to persistentstorage of a dirty data item is coordinated using the master assigned tothe data item. In particular, a node that desires to write a dirty dataitem to persistent storage sends a write-request message to the masterassigned to the data item. The master may (1) grant the requesting nodepermission to perform the write, or (2) inform the requesting node thatanother node has already written to persistent storage a version that isat least as recent as the dirty version stored in the requesting node.

More specifically, when a dirty data item is “pinged out” of a node'scache, i.e. another node requires a current version of the same dataitem for read(S lock) or write(X lock), the status of the data item inthe sending node's cache is changed to PI. The data item still remainsin the dirty or checkpoint queue. When a clean data item is pinged out,the data item can be either marked free or can remain in the cache tosatisfy consistent snapshot reads.

The master of the data item records the version number of the data itemwhen the data item is pinged out. Typically this version number is a logsequence number (LSN), a system commit number (SCN) or a globally uniquetimestamp that can be used to correlate the version of the data itemwith the changes in the redo log. The checkpoint or the cache writingsubsystem will eventually need to write out the PI (or some successorthereof) since the data item is still on the dirty or checkpoint queue.

According to the direct write approach, a message is sent to the masterwhich would either return with a status that a more recent version ofthe data item has been written, or grant write permission to therequesting node. Further write requests for the same data item fromother nodes are queued until the writing node responds to the lockmanager with a write completion status. After a PI is written topersistent storage, the master of the data item records the versionnumber of the PI as the version that is currently on persistent storage.

Referring to FIG. 1, it is a block diagram illustrating a system thatemploys the direct write approach. Nodes 1, 2 and 3 have stored in theircaches versions V1, V2, and V3, respectively, of a particular data item.Assume that V3>V2>V1, where A>B means that A is a newer version of thedata item than B.

Master 100 is the master assigned to the data item. In the scenarioillustrated in FIG. 1, nodes 1 and 3 send write-requests to master 100.To prevent multiple nodes writing the same data item at the same time,master 100 may contain, for example, a write-request queue for each dataitem. The write requests received for the data item are stored in thewrite-request queue and processed serially by the master. In theillustrated example, master 100 processes the write-request from node 3first, while the write-request from node 1 remains in the write-requestqueue. Master 100 responds to the write-request of node 3 by sendingnode 3 a write-perform message that grants node 3 permission to write V3to persistent storage.

While the write-request has been granted to node 3, master 100 does notgrant write-to-persistent storage permission to any other node.Therefore, the write-request from node 1 remains pending in thewrite-request queue.

After node 3 has written V3 to persistent storage, node 3 sends master100 a write confirm message indicating that the write-to-persistentstorage operation has been completed, and that the write-to-persistentstorage permission is being released by node 3. Because V3 was newerthan V1 and V2, V1 and V2 were covered by the writing of V3.

Master 100 then proceeds to process the next write-request in the queue.In the present example, master 100 processes the write-request from node1. The write-request of node 1 is a request to write V1. Because V1 wasalready covered by the write of V3, master 100 sends awrite-notification message to node 1 indicating that V1 is alreadycovered. In response to the write-notification message, node 1 removesthe entry for V1 from its checkpoint queue without writing V1 topersistent storage. Because node 1 now knows that V1 is covered, node 1need not retain a copy of V1 in memory.

According to one embodiment, node 2, which contains V2 that was coveredby the writing of V3, is not sent a write-notification message untilnode 2 sends master 100 a write-request for V2.

Indirect Write Approach

Using the direct write approach, each node sends a write-request messagefor each entry in the node's checkpoint queue. In some cases, the nodewill receive a write-perform message in response to the write-request.When a write-perform message is received, the requesting node mustperform a write operation. In other cases, the requesting node willreceive a write-notification in response to the write-request. When awrite-notification message is received, the requesting node does notneed to perform the write operation.

The indirect write approach attempts to increase the percentage ofwrite-requests that are answered with write-notification messages. Toachieve this, master 100 is selective with respect to the node that isasked to perform a write operation. In particular, master 100 mayrespond to a write-request message from one node by sending awrite-perform message to another node. The node to which a write-performmessage is sent may be selected based on a variety of factors, includingthe recentness of the version of the data item stored in the cache.According to one embodiment, master 100 always sends the write-performmessage to the node that contains the current version of the data item,regardless of the node that sent the write-request message.

More specifically, according to one embodiment, the master forwardswrite requests to either the node that has the highest version among thepast images, or preferably the exclusive lock (X) holder (which wouldhave the current version of the data item). Forwarding the write requestto the highest PI rather than to the exclusive lock holder leaves thecurrent data item continuously available for modification.

While a data item is being written to persistent storage, it may not bemodified; therefore, to write a current data item that may be modifiedfurther, it is necessary either to lock it to prevent modifications, orto “clone” it to have changes made to a different copy. Locking isundesirable; if cloning is possible, it is preferable to direct thewrite request to the node that has the current data item (i.e X lock orS lock).

Having the current version of the data written to persistent storageallows a persistent storage write to cover as many changes as possible.When the write to persistent storage completes, a message is sent to themaster with a write completion status and the version number of the dataitem that was written. The master records the version number that is onpersistent storage and sends write notification messages to all nodesthat have a PI version of the data item that is now covered by thepersistent storage write. When a node receives a write notification, thenode can correctly advance its checkpoint record and release the PI dataitems, provided all data items on its dirty or checkpoint queue prior tothe checkpoint record have either been written to persistent storage orhave received write notifications from the master due to writes of thesame data item in other nodes. The master logically maintains a queue ofwrite requests when a data item is being written, but only needs torecord the version number of the highest write request that it hasreceived.

For example, in the scenario illustrated in FIG. 2, node 3 has not senta write-request message for V3 to master 100. However, in response tothe write-request message from node 1 to write version V1 of the dataitem, master 100 selects node 3 to be the node to write the data item.Node 3 responds by writing V3 of the data item, and sending awrite-confirm message to master 100. Master 100 then sends awrite-notification message to node 1.

Because node 3 was selected for writing V3 to persistent storage, bothV1 and V2 are covered. In contrast, if (according to the direct writeapproach) master 100 had given node 1 permission to write V1, then V2and V3 would not be covered. When it came time to write V2 and V3 topersistent storage, separate write operations would have to beperformed.

The indirect write approach also attempts to reduce the number ofwrite-request messages that have to be sent to master 100 bypreemptively sending write-notification messages to interested nodesthat have not sent write-request messages, as well as to those thathave. For example, in the scenario illustrated in FIG. 2, using theindirect write approach, master 100 would also send a write-notificationto node 2, even though node 2 has not sent a write-request for V2.According to one embodiment, master 100 sends write-notificationmessages to all of the interested nodes.

When an interested node receives a write-notification, it removes theentry for the corresponding version of the data item from its checkpointqueue. Using the indirect write approach, many of the entries in thecheckpoint queue may be removed in this manner before a write-requestwould have to be sent for the entries. Consequently, the number ofwrite-request messages that are sent by a node may be significantly lessthan the number of entries that were placed in its checkpoint queue.

Owner-Based Writes

In both the indirect write approach and the direct write approach,write-requests messages are sent to the master of the data item evenwhen the data item has been dirtied only in one node's cache. In manydatabase systems a significant fraction of the database working set maybe partitioned between the nodes either by partitioning the internalpersistent storage structures between the nodes (e.g. separate data itemfreelists for each node) or by application level routing of transactionsto nodes. In such systems, a data item will frequently have been dirtiedin only one node's cache. The owner-based write approach avoids the needto send write-requests under these circumstances.

The owner-based write approach causes all writes of a data item to bemade by the node that is currently designated to be the “owner” of thedata item. In contrast to the direct and indirect write approaches, whenthe owner of the data item desires a version of the data item to bewritten, the owner is allowed to write the data item to persistentstorage without sending a write-request message to the master of thedata item.

Various factors may be used to select the node that acts as the owner ofthe data item. According to one embodiment, the owner for a data item isselected based on the following rules:

(1) if a node has been granted the exclusive lock for the data item,then that node is considered the owner of the data item;

(2) if there are no exclusive lock holders, i.e. there are multipleshare lock (S) holders, then the node that had the exclusive lock on thedata item most recently is selected as the owner of the data item; and

(3) if the data item has never been dirtied by any node, then there isno owner for the data item.

In a node that is the owner of a data item, the data item is linked tothe node's dirty or checkpoint queue even when it may not have beendirtied in that node.

After the owner of the data item writes the data item to persistentstorage, the owner determines whether the data item was “globallydirty”. A data item is globally dirty if any modifications made by anynode other than the owner have not been saved to persistent storage bythat node. If the data item was globally dirty, then the owner sends awrite-confirm message to the master. The master may then sendwrite-notifications to the interested nodes. If the data item was notglobally dirty, then the owner need not send a write-confirm message tothe master.

Various techniques may be used to allow the owner of a data item todetermine whether the data item was globally dirty. According to oneembodiment, a global dirty flag is associated with the data item. When anode sends a dirty version of a data item to another node withoutwriting the data item to persistent storage, the sending node sets theglobal dirty flag of the data item to TRUE. To determine whether a dataitem is globally dirty, the owner merely needs to inspect the globaldirty flag associated with the data item. If the version of the dataitem that is written to persistent storage is either (1) the currentversion of the data item, or (2) the latest PI version, then the ownersets the global dirty flag to FALSE after writing the data item topersistent storage.

The global dirty flag of a data item may be stored in a variety of ways.For example, when the data item is a data item in a database system, theglobal dirty flag may be stored in (1) the block header of the blockthat stores the data item, (2) the data item control block of the dataitem, (3) the lock structures in a local lock manager when the lock isgranted to the new owner of the data item, etc.

Referring to FIG. 3 a, it illustrates a scenario in which the owner of adata item (node 3) desires to write a data item to persistent storage,where the global dirty flag is set to FALSE. As can be seen in FIG. 3 a,under these circumstances, node 3 need not ask permission from master100. In addition, node 3 need not notify master 100 that thewrite-to-persistent-storage operation was performed.

Referring to FIG. 3 b, it illustrates a scenario in which the owner of adata item (node 3) desires to write a data item to persistent storage,where the global dirty flag is set to TRUE. In the illustrated scenario,nodes 1 and 2 have dirty versions V1 and V2 of the data item that areolder than the version V3 stored in node 3. Similar to the scenarioshown in FIG. 3 a, in this scenario node 3 need not request permissionto write V3 to persistent storage. However, because the global dirtyflag was TRUE, node 3 sends a write-confirm message to master 100 afterwriting V3 to persistent storage. Master 100 then sendswrite-notification messages to nodes 1 and 2. After writing V3 topersistent storage, node 3 sets the global dirty flag to FALSE.

Referring to FIG. 3 c, it illustrates a scenario in which a non-owner ofa data item (node 1) desires the data item to be written to persistentstorage. In this scenario, node 1 sends a write-request message tomaster 100. Master 100 then sends a write-perform message to the owner(node 3) of the data item. Node 3 writes V3 to persistent storage, setsthe global dirty flag to FALSE, and sends a write-confirm message tomaster 100. Master 100 then sends write-notification messages to theinterested nodes (nodes 1 and 2).

Role-Based Approach

The owner-based write approach avoids the need for the owner of a dataitem to get permission from the master of the data item before writingthe data item to persistent storage. However, to avoid the possibilityof two nodes attempting to write the data item to persistent storage atthe same time, the ownership of the data item is not allowed to changewhile the data item's current owner is writing the data item topersistent storage. Consequently, in systems where the holder of anexclusive lock is considered to be the owner, the exclusive lock cannotbe transferred to another node while the data item's current owner iswriting the data item to persistent storage. As a result, the transferof the modify permission to a subsequent node that desires to modify thedata item is delayed until the data item is written to persistentstorage. Such delays reduce the overall performance of the system. Inaddition, it is undesirable for the owner of a data item to have to linkthe data item in its dirty queue even though the owner may not havedirtied the data item.

The role-based approach separates (1) ownership of an exclusive lock ina data item from (2) permission to write the data item to persistentstorage without sending a write-request. Because ownership of anexclusive lock in a data item is separated from permission to write thedata item to persistent storage without sending a write-request, theexclusive lock ownership of a data item may be transferred between nodeseven when a write-to-persistent storage operation is in progress.

According to the role-based approach, a lock role is assigned to eachlock. The lock role is “local” if the data item could be potentiallydirty only in one node's cache. Hence, when a lock on a data item isgranted to a node for the first time in the entire system, the lock isgranted with local role. A data item under a lock with local role can beboth written to persistent storage and read from persistent storage bythe node that holds the lock without master intervention.

When a data item is pinged out from a node's cache because of a lockrequest from a different node, the role for the lock is converted to“global” if the data item is dirty in the holding node's cache.Otherwise, the lock that is transferred with the data item remains underlocal role. Thus, a data item needs to be under global role only ifthere is at least one PI for the data item in the multi-node system.

When a PI data item or a current data item in global role needs to bewritten to persistent storage, its holding node sends to the master awrite-request message with the version number of the data item thatneeds to be written. The master can forward the write request to eitherthe node that has the current data item (X lock holder) or any PI whoseversion number is greater than or equal to the version number of the PIthat needs to be written. When the write completes, the master sendswrite notifications to all nodes that have PIs that are covered by theversion of the data item that is written to persistent storage.

Since the node that has the exclusive lock in global role also needs tocoordinate its write-to-persistent storage operations with the master,an exclusive lock can be transferred to another node even while the dataitem under the exclusive lock is in the middle of being written. For thesame reason, a node does not link a data item into its checkpoint ordirty queue unless it has been dirtied in that node. When a dirty dataitem is pinged out while it is being written under local role, the lockrole is switched to global and the in-progress write is communicated tothe master.

Referring to FIG. 4 a, it illustrates a scenario in which the holder ofa local-mode lock (node 3) desires to write a version of the data itemto persistent storage. Because the lock held by node 3 is in local mode,node 3 writes the data item to persistent storage without askingpermission from master 100. Node 3 also need not inform master 100 thatthe data item was written to persistent storage.

Referring to FIG. 4 b, it illustrates a scenario in which the holder ofa global-mode lock (node 3) desires to write a version V3 of a data itemto persistent storage. Because the lock mode is global, it is possiblethat another node is writing the data item. Therefore, node 3 sends awrite-request message to master 100. In response to the write-requestmessage, master 100 selects a node to write out the data item.Preferably, master 100 selects a node that has a version of the dataitem that is at least as recent as V3. In the present example, V3 is thecurrent version of the data item. Consequently, master 100 sends back tonode 3 a write-perform message.

In response to the write perform message, node 3 writes V3 to persistentstorage, and sends a write-confirm message back to master 100. Master100 then sends a write-notification message to the interested nodes(nodes 1 and 2).

If the version of the data item that is written to persistent storage isthe current version, then the node that writes the data item topersistent storage also converts the lock from global mode to localmode. This conversion may be performed when the current version iswritten to persistent storage. The node that writes the current versionto persistent storage is able to determine that the node is writing thecurrent version based on the fact that the node holds an exclusive lockon the data item. In the present example, V3 is the current version, soafter writing V3 to persistent storage, node 3 converts the mode fromglobal to local.

Referring to FIG. 4 c, it illustrates a scenario in which a node (node1) that is not holding the current version of a data item requests forthe data item to be written to persistent storage. The sequence ofevents shown in FIG. 4 c are the same as those in FIG. 4 b, except thatthe write-request message comes from node 1 rather than node 3.

As illustrated in FIG. 4 b, in contrast to the owner-based approach,under the role-based approach the owner of an exclusive lock on a dataitem must still seek permission to write the data item from the master100 when the lock is in global mode. However, unlike the owner-basedapproach, a data item (and the exclusive lock thereto) may betransferred from one node to another without waiting for awrite-to-persistent storage operation to complete.

For example, FIG. 4 d illustrates the same scenario as FIG. 4 c, exceptthat a node (node 4) has requested exclusive ownership of the data item.Node 3 is able to transfer the data item to node 4 even when node 3 isin the process of writing V3 to persistent storage in response to thewrite-perform message. With the exclusive write lock, node 4 may proceedto modify the data item to create version V4. However, because the modeis global, node 4 cannot write V4 to persistent storage.

In FIG. 4 c, upon receipt of the write-confirm message from node 3,master 100 sends a convert-to-local message to node 4. In response toreceiving the convert-to-local message, node 4 converts the mode fromglobal to local. After the mode has been changed back to local, node 4can write the data item to persistent storage and read the data itemfrom persistent storage without any permission from master 100.

In an alternative embodiment, master 100 does not send aconvert-to-local message in response to the write-confirm message.Without the convert-to-local message, the mode of the exclusive lockwill remain global in node 4. Because the mode is global, node 4 willsend a write-request to master 100 if node 4 wishes to write V4 topersistent storage. In response to the write-request message, master 100may send the convert-to-local message to node 4. After the mode isconverted to local, node 4 may write V4 without further permission.

Delayed Write Notifications

In the scenarios presented above, it was mentioned that the sending ofwrite-notification messages can be performed immediately to allinterested nodes, or the sending may be deferred to some or all of theinterested nodes. According to one embodiment, when awrite-to-persistent storage operation is performed, a write-notificationmessage is immediately sent only to those nodes that have requested awrite for a PI that is covered by the write that has been performed. Forexample, in FIG. 1, master 100 immediately sends a write-notificationmessage to node 1, but not to node 2.

The version number of the data item on persistent storage can later becommunicated from the master to the other interested nodes using any oneof a variety of techniques. For example, the version number of the dataitem on persistent storage can be communicated as part of (1) lock grantmessages for new lock requests, or (2) ping messages when the currentversion of a data item needs to be sent to another node. Hence, when theother interested nodes need to write or replace their PIs, they candiscard their PIs by communicating only with the local lock manager.

Batched Messages

Another technique for reducing the number of messages that arecommunicated between a master and interested nodes involves batching thewrite-request messages and the write-notification messages from and tothe master into fewer larger messages in order to reduce the number ofmessages. For example, if node 1 desires to advance its checkpoint queueby three entries, node 1 may send a single write-request message tomaster 100 that identifies all three data items (and their respectiveversions) that must be written to persistent storage. Similarly, if node1 is interested in three write-to-persistent storage operations thathave been completed, master 100 may send a single write-confirm messageto node 1 that identifies the three data items (and their respectiveversions) that have been written to persistent storage.

Checkpoint Queues: Managing Multiple Past Images of the Same Data Item

In the scenarios presented above, it was assumed that each node's cachehas at most one PI for each data item. In reality, a data item maycirculate several times through multiple nodes before some version ofthe data item is written to persistent storage. It would be correct tocreate a PI every time a dirty data item is pinged out to another nodeand have entries for several PIs at different positions in the dirty orcheckpoint queue in a node's cache.

For example, FIG. 5 illustrates a scenario in which the checkpoint queue500 of a node has three entries for a particular data item (data item5). In particular, checkpoint queue 500 has a head 502 and a tail 504and three entries 506, 508 and 510 that correspond to versions V1, V6and V8 of data item 5. Similarly, FIG. 6 illustrates a scenario in whichthe checkpoint queue 600 of another node has two entries for data item5. In particular, entries 606 and 608 correspond to versions V3 and V7of data item 5.

For the purpose of explanation, it shall be assumed that checkpointqueue 500 is the checkpoint queue for a node A (not shown), and thatcheckpoint queue 600 is the checkpoint queue for a node B (not shown).

The master of a data item is updated with the version number of the mostrecent PI that is created after a dirty data item is transferred toanother node. Thus, when node A creates V1 of data item 5 and transfersdata item 5 to another node, the master of data item 5 is updated toindicate that node A has V1. When node A subsequently creates V6 of dataitem 5 and transfers data item 5 to another node, the master of dataitem 5 is updated to indicate that node A has V6. Similarly, when node Asubsequently creates V8 of data item 5 and transfers data item 5 toanother node, the master of data item 5 is updated to indicate that nodeA has V8.

However, a PI occupies memory in the cache and cannot be replaced untilit or a more recent version is written to persistent storage. Hence,when a dirty data item is transferred out of a cache, the newly createdPI may be merged with (replace) the previous PI, if one exists. Thecheckpoint entry associated with the merged PI, however, must remain inthe same position in the dirty or checkpoint queue as the entry of theearliest version that was involved in the merger, because a checkpointcannot be considered complete until the changes that were made to thedata item when the first PI was created are reflected on the persistentstorage version of the data item. Further, the merged entry cannot beremoved from the checkpoint queue until the latest version in the mergeris covered by a write-to-disk operation.

For example, FIG. 7 illustrates checkpoint queue 500 were the entries506, 508 and 510 for versions V1, V6 and V8 of data item 5 are mergedinto a single entry 702. The single entry 702 is located at the positionthat was occupied by entry 506, because entry 506 was the earliest entryinvolved in the merger.

Partially-Covered Merged Entries

When PIs of a data item are merged, it is possible that when a versionof the data item is written to persistent storage on a different node,the version covers some but not all of the changes that are reflected inthe merged PI. For example, if node B writes V7 of data item 5 topersistent storage, then only the changes associated with V1 and V6 ofthe merged entry 702 are covered. The changes that are associated withV8 are not covered.

When the persistent storage version completely covers the changescontained in a merged PI, the entry for the PI can be discarded and thecheckpoint can be advanced past the earliest change made in the PI. Forexample, if V9 of data item 5 had been written to persistent storage,then merged entry 702 could be discarded.

On the other hand, when a persistent storage write covers only some ofthe changes of a merged PI, then the entry for the merged PI cannot bediscarded. For example, even though the writing of V7 to persistentstorage would allow non-merged entries 506 and 508 to be removed fromcheckpoint queue 500, it does not allow the merged entry 702 to beremoved from checkpoint queue 500.

Although the entry for a partially covered merged PI cannot bediscarded, the entry can be moved in the dirty or checkpoint queue tothe position of the entry for the version that is just after the versionthat was written to persistent storage. For example, after V7 of dataitem 5 is written to persistent storage, entry 702 can be moved to theposition in checkpoint queue 500 at which the entry for V8 of data item5 (i.e. entry 510) had been located. This allows the checkpoint toproceed until the first entry that is not covered by the written-to-diskversion, without being blocked by the entry for the merged PI.

Avoiding the Creation of Partially-Covered Merged Entries

In some systems, the dirty or checkpoint queues are implemented as alinked list. It may be expensive, in terms of CPU usage, to scan thelinked list and insert a merged entry in the correct position within thequeue. An in-memory index can be implemented to facilitate this, butthat would cause extra overhead when linking data items to thecheckpoint queues.

According to one embodiment, the overhead associated with movingpartially covered merged entries is avoided by avoiding the creation ofpartially covered moved entries. Specifically, when a merge operation islikely to create a merged entry that would be partially covered, themerge operation is not performed.

According to one embodiment, when (1) a version of a data item is beingwritten to persistent storage, and (2) the data item is transferredbetween nodes, the master communicates the version number of the dataitem that is currently being written to persistent storage (the“being-written” version) to the node to which the data item is beingtransferred (the “receiving” node). The receiving node thus knows not tomerge any version of the data item that is the same as or earlier thanthe being-written version with any version of the data item that islater than the being-written version.

Referring again to FIGS. 5 and 6, assume that node A is in the processof writing V6 of data item 5. Before the write operation is complete,node A sends data item 5 to node B, and node B modifies the receivedversion of data item 5 to create V7 of data item 5. The master informsnode B that V6 of data item 5 was written to persistent storage when themaster sends a ping to node B. Consequently, node B does not merge V7 ofdata item 5 with V3 of data item 5, because the resulting merged dataitem would only be partially covered by the writing of V6. Because thewriting of V6 fully covers V3, after the writing of V6 is completed,node B may discard V3, and remove entry 606 from queue 600.

Thus, while a write-to-persistent storage operation is in progress, PIsand entries associated with versions that are at least as old as thebeing-written version may be merged with each other, and PIs and entriesassociated with versions that are newer than the being-written versionmay be merged with each other. However, PIs associated with versionsthat are at least as old as the being-written version should not bemerged with the PIs associated with versions that are newer than thebeing-written version.

Using this technique in a system where the holder of the most recentversion always performs the write-to-persistent storage operationensures that no merged PIs will ever be partially covered by awrite-to-persistent storage operation. Specifically, when a node ispinged to send a data item that is undergoing a write-to-persistentstorage operation, it will not merge the new version of the data itemwith older versions. If the data item is not undergoing awrite-to-persistent storage operation, then the received data item willbe the most recent version, and no other node will thereafter be askedto write an earlier version of that data item to persistent storage.

An alternative scheme to avoid writes covering partial changes is toheuristically determine when to create new checkpoint queue entriesrather than merging with existing checkpoint queue entries. For example,assume that a checkpoint queue entry exists for versions V7 of data item3. It may be necessary to determine whether to create a new entry for anew version of data item 3, or merge the new version with the existingentry. The decision of whether to merge may be decided heuristicallybased, for example, on how old the first change made to the existingentry is with respect to (1) the most recent change present in the redolog and (2) the earliest change made to the data item at the head of thedirty or checkpoint queue. This heuristic estimates the probability thatthe PI associated with the existing entry would be written (or coveredby a write) fairly soon, and enables the node to extend the checkpointpast the first change in the PI.

For example, if the most recent change in the redo log corresponds to atime that is much later than V7, and the data item at the head of thecheckpoint queue is associated with a time that is close to V7, thenthere is a higher probability that the PI associated with the existingentry will be written (or covered by a write) soon, and therefore aseparate entry should be made for the new version. On the other hand, ifthe most recent change in the redo log corresponds to a time that isclose to V7, and the data item at the head of the checkpoint queuecorresponds to a time that is much earlier than V7, then there is alower likelihood that the PI associated with the existing entry would bewritten (or covered by a write) soon. Therefore, the new version shouldbe merged into the existing entry.

Single-Node-Failure Checkpoint Queues

As mentioned above, the entry at the head of a checkpoint queuedetermines the position, within a redo log, where recovery processingmust begin after a failure. For an accurate recovery, it is safe tobegin processing the redo log from the location that corresponds to theentry at the head of the checkpoint queue regardless of how many of thenodes within a cluster were involved in the failure.

According to one embodiment, a checkpoint mechanism is provided to keeptrack of two checkpoints for each node: a multiple-failure-checkpointand a single-failure checkpoint. The multiple-failure-checkpointindicates the position to begin processing the redo of the node after amultiple-node failure involving the node. The single-failure-checkpointindicates the position to begin processing the redo log of the nodeafter a single-node failure of the node.

As shall be described hereafter, entries may be removed from thesingle-failure-checkpoint queue under circumstances that do not allowthem to be removed from the multiple-failure-checkpoint queue.Consequently, the single-failure-checkpoint will typically be advancedfurther than the multiple-failure-checkpoint. Because the single-failurecheckpoint is further advanced, maintaining thesingle-failure-checkpoint results in less work that has to be performedto recover from a single node failure.

With respect to advancing the checkpoints, the multiple-node-failurecheckpoint of the node does not change when a node transfers a dirtydata item to another node. Because the data item was dirty, there is anentry for the data item in the multiple-failure-checkpoint queue. Thatentry remains in the multiple-failure-checkpoint queue after the dirtydata item is transferred.

In contrast, the entry associated with a dirty data item is removed fromthe single-failure-checkpoint queue when the dirty data item istransferred to another node. It is safe to remove the entry for thetransferred dirty item from the single-failure-checkpoint queue becausethe changes made to the dirty data item will not be lost if only thetransferring node fails. In response to the failure of only thetransferring node, the changes made by the transferring node arereflected in the version of the data item sent to the receiving node.Under these circumstances, the responsibility for ensuring that thechanges are saved to persistent storage are transferred with the dataitem. Thus, even if the receiving node does not perform any furthermodifications to the data item, the receiving node must either (1)ensure that the changes made by the transferring node (or redo for thechanges) are written to persistent storage, or (2) transfer the dirtydata item (and the responsibilities) to yet another node.

The transfer of a dirty data item to another node allows thetransferring node to remove the entry for the transferred data item fromits single-node-failure checkpoint queue. Consequently, a node thatdesires to advance its single-node-failure checkpoint queue can simplytransfer to another node the dirty data item that corresponds to theentry at the head of its single-node-failure checkpoint queue. Thetransfer of the dirty data item may be performed for this purpose evenif the node that receives the dirty data item never requested the dataitem.

The two checkpoints may be implemented in a variety of ways, and thepresent invention is not limited to any particular implementation. Forexample, the single-failure-checkpoint queue and themultiple-failure-checkpoint queue may be maintained as two entirelyseparate queues. Alternatively, a single “combined” queue of entries maybe maintained to serve both as the single-failure-checkpoint queue andthe multiple-failure-checkpoint queue. When a combined queue is used, apointer may be used to identify, within the combined queue, which entryis at the head of the single-failure-checkpoint queue. When entries areremoved from the multiple-failure-checkpoint queue, they are removedfrom the combined queue. When entries are removed from thesingle-failure-checkpoint queue, they are marked accordingly, but arenot removed from the combined queue.

Bin-Based Batching

According to the bin-based batching approach, two separate checkpointqueues are maintained in a node: a globally-dirty checkpoint queue and alocally-dirty checkpoint queue. The locally-dirty checkpoint queue of anode includes entries for data items that are dirty only in that node.The globally-dirty checkpoint queue of a node includes entries for dataitems that have also been dirtied in other nodes.

According to one embodiment, the entries in the globally-dirtycheckpoint queue are grouped into “bins”. Each bin is associated with arange of time, and contains those entries that are for versions of dataitems that were first dirtied within that range of time. Thus, if amerged entry corresponds to those versions of a data item that were madewhen the data item was dirtied at times T7, T9 and T12, then the mergedentry would fall into the bin that corresponds to the time range thatincludes T7, since T7 is the “first-dirtied time” covered by the entry.

For example, FIG. 8 illustrates a globally-dirty checkpoint queue 800 ofa node X that has been divided into bins 812, 814 and 816. Bin 812 isassociated with the time range T15 to T25 and contains entries for theglobally dirty data items that have first-dirtied times between T15 andT25. Bin 814 is associated with the time range T16 to T35 and containsentries for the globally dirty data items that have first-dirtied timesbetween T16 and T35. Bin 816 is associated with the time range T36 toT45 and contains entries for the globally dirty data items that havefirst-dirtied times between T36 and T45.

According to an embodiment, each bin is assigned a version number. Theversion number of a bin may be, for example, the first-dirtied timevalue of any entry in that bin. For example, bin 812 includes threeentries 805, 806 and 807 that are respectively associated with V1 ofdata item 1, V1 of data item 5, and V3 of data item 8. Assume that V1 ofdata item 1, V1 of data item 5, and V3 of data item 8 were first dirtiedat times T17, T19 and T23, respectively. In this scenario, T23 is thehighest first-dirtied time of any PI in bin 812. Hence, bin 812 would beassigned the version number T23.

According to one embodiment, the number of write-request messages isreduced by having the persistent storage writing subsystem issuewrite-requests to a master on a bin-by-bin basis, rather than on anentry-by-entry basis. For example, to advance checkpoint queue 800, thenode X sends the master a single write-request message for the writingof the data items that correspond to all entries in bin 812. Thewrite-request message may simply identify bin 812 by the version numberT23 (and not the specific entries within the bin). In response to thewrite-request, the master sends write-perform messages to the currentlock holders of all data items that have a PI whose first-dirtied timeis less than or equal to the version number specified in thewrite-request. In the present example, the master sends write-performmessages to the current lock holders of all data items that have a PIwhose first-dirtied time is less than or equal to T23.

When each node finishes writing to disk all dirty data items whoseearliest change is on or before T23, the node sends a write-confirmmessage to the master. When the master receives write-confirm messagesfrom all nodes to which write-perform messages were sent, the mastersends write-notification messages to all nodes to inform them that therequested writes have been completed. In response, every node can emptythe corresponding bin. For example, when node X is informed that alldata items with first-dirtied times on or before T23 have been writtento disk, then node X may empty bin 812. Bin 812 may be emptied by (1)discarding all entries that do not cover changes made after T23, and (2)moving to other bins those entries within bin 812 that do cover changesmade after T23. For example, if entry 806 was a merged entry thatcovered changes made at T19 and T40, then when bin 812 is emptied, entry806 is moved to bin 814.

According to one embodiment, the master tracks both (1) thefirst-dirtied time of a PI and (2) the version number associated withthe last change to the PI (the “last-dirtied time”). For example, formerged entry 702, the master would know that merged entry is for versionV8 (the latest version in the merged entry) and version V1 (the earliestversion in the merged entry). In such an embodiment, when a nodereceives a write-notification from the master with a version number of abin, it empties the bin by discarding all entries in the bin whoselast-dirtied times are less than or equal to the bin version number, and(2) moving all entries in the bin whose last-dirtied times are greaterthan the bin version number into the next bin in the queue. In thisscheme, when a new PI is created because a dirty data item istransferred to another node, the entry for the new PI can always replacethe entry for the older PI, if any, in the older PI's bin because theentry for the resulting merged PI can then be easily moved to itsappropriate bin when there is a write that partially covers changescontained in the PI.

Bin-based batching is generally more suitable to multi-node systems thatuse a global master rather than a distributed lock manager. The messagesto the current lock holders can be easily batched because they aregenerated at the same time. In essence, instead of tracking the versionnumbers of data items that are on persistent storage and the versionnumbers of data items that are in the process of being written, themaster also tracks the persistent storage version number for allglobally dirty data items, much like a checkpoint record tracks thechanges for all the dirty data items in a node.

Recovery

It is important to keep track of the write-to-disk operations that areperformed in a multi-node system. Such information is critical, forexample, for determining which entries can be removed from checkpointqueues, and for determining whether past images of data items can bewritten-to-disk and/or deallocated (“flushed”) from cache. Specifically,a version of a data item should never be written to disk if a laterversion of the data item has already been written to disk. Further, PIversions of a data item may be flushed from cache when a more recentversion of the data item has been written to disk.

Under certain circumstances, it can be unclear whether a write-to-diskoperation is successfully performed. For example, if a node writing adata item to disk fails during the write operation, it may be unclearwhether the failure occurred before or after the write operation wassuccessfully completed. Similarly, if the node on which the master of aparticular data item resides fails, the failure may result in a loss ofinformation about the data item. Such information may includeinformation that indicates the last version of the data item to bewritten to disk.

When a situation occurs where it is unclear whether a write-to-diskoperation was successfully performed, the issue may be resolved byscanning the data items on disk to determine their versions. However,scanning the disk as part of the recovery operation would consume asignificant amount of time and resources, and may unduly delay theavailability of the data.

According to one aspect of the invention, the need to scan the on-diskdata items is avoided by (1) if it is unclear whether a particularversion of a data item has been written to disk and the recoveryinformation (e.g. redo log) indicates that the particular version waswritten to disk, causing the recovery process to assume that theparticular data item was successfully written to disk, and (2) markingall earlier cached versions of that data item as “suspect”. After therecovery operation, the system may then proceed under the oppositeassumption. Specifically, the system proceeds under the assumption thatthe particular version of the data item was not written to disk.However, prior to writing any suspect version of the data item to disk,the system reads the version of the data item that resides on disk. Ifthe on-disk version of the data item is more recent, then thewrite-to-disk operation is not performed, and the master is informed ofwhich version is on disk. Optionally, the master then sendswrite-notification messages to all nodes that hold versions that arecovered by the version that is on the disk. On the other hand, the dataitem is recovered.

Similarly, when a node requests the current version of a data item, therequesting node cannot be supplied a suspect version of the data itembecause the disk may contain a more recent version of the data item.Instead, the on-disk version of the data item is read from disk. If theversion of the data item that is read from disk is the most recentversion, then that version is provided to the requesting node. If theon-disk version of the data item is not the most recent version, thenthe most recent version is created based on the recovery informationmaintained in the redo log of the node that had failed.

Managing Checkpoints without Retaining Past Images

In many of the scenarios given above, it was assumed that each node isconfigured to retain a PI until the PI is covered by a write-to-diskoperation. However, according to one embodiment of the invention, suchPIs are not retained.

Specifically, each node maintains a globally-dirty checkpoint queue anda locally-dirty checkpoint queue. The dirty data items associated withthe entries in the locally-dirty checkpoint queue are retained untilcovered by a write-to-disk operation. However, the PIs associated withthe entries in the globally-dirty checkpoint queue need not be retainedin that manner.

In this embodiment, the right to perform write-to-disk operations istied to the mode of the lock held on the data item, as described above.Specifically, a node has the right to perform a write-to-disk operationfor a data item if (1) the node holds the exclusive lock for the dataitem, or (2) no node holds the exclusive lock for the data item, andthis node was the most recent node to hold the exclusive lock.

Since a node will have the exclusive lock for all data items that arelocally dirty, the node will be able to write the data items associatedwith the locally-dirty queue to disk without master intervention. Thenode may also have an exclusive lock, or have held the most recentexclusive lock, for a data item associated with an entry in theglobally-dirty queue, and therefore be able to write that data item todisk without master intervention.

Because the node does not retain a PI when a dirty data item is pingedout of the cache, special recovery processing is required. Specifically,when the current version of the data item is lost during data itemtransfer or due to node failure, the system applies changes from themerged redo logs of all nodes to the data item on persistent storage inorder to reconstruct the current version of the data item. The location,within each redo log, where recovery processing must begin is determinedby a checkpoint associated with the node. A checkpoint in a node cannotbe considered complete unless a version of the data item containingchanges made in the node prior to the checkpoint is on persistentstorage. Hence, when a dirty data item is pinged out to another node,rather than retaining a past image of the data item in any checkpointqueue, the data item itself may be discarded, and the data item headeror control block is linked into the globally-dirty queue.

The globally-dirty queue is ordered by the first-dirtied timesassociated with the entries and is similar to the locally-dirty queue,except that there is no real data item associated retained for each ofthe entries (i.e. the data item's contents are not present in the cacheof the node). The checkpoint in a node will be the lower of thefirst-dirtied time of the entry at the head of the locally-dirty queueand the first-dirtied time of the entry at the head of theglobally-dirty queue.

When a node wants to advance its checkpoint, it can write the data itemsin the locally-dirty queue without master intervention (because there isnever a possibility of two nodes writing the same data item at the sametime) or send a write request to the master for writing out the dataitem at the owner node that corresponds to a more current version of thedata item header in the globally-dirty queue.

According to an alternative embodiment, two checkpoint records arestored in each node (one for each queue). The first checkpoint recordwould indicate a time TX, where all changes made to data items that arepresently dirty in the node's cache prior to TX have been recorded onthe version of the data item that is on persistent storage. The secondcheckpoint record would consist of the list of data items, along withthe version numbers of the first change made in this node, that wereonce dirtied in this node but have since been pinged out and not writtento persistent storage. The cache loses track of the dirty data item onceit has been pinged out, while still leaving the lock open in the master(i.e. the locks are not closed until there is a write notification).

On a node failure, the starting position for scanning the redo log onthe failed node is computed by determining the lesser of (1) theposition in the log as determined by the first checkpoint record (callit a local checkpoint record) and (2) the positions in the log asdetermined by the earliest change made to the list of the data items inthe second checkpoint record (which may be considered that particularnode's part of a global checkpoint record).

During recovery, only those log records that correspond to the dataitems present in the global checkpoint record need to be considered forpotential redo for the portion of the log between the global checkpointrecord of a node to the local checkpoint record of the node (assumingthat the global checkpoint record is behind the local checkpointrecord). Once the local checkpoint record is reached, all log recordsneed to be considered for potential redo until the end of the log isreached.

This scheme is superior to prior approaches in that it limits the listof data items in the second checkpoint record to only data items thathad been previously dirtied in this node (as opposed to all dirty dataitems in the entire system). Second, each node's global checkpointrecord can be written independent of other nodes (i.e. there is no needfor coordinating a global master or GLM checkpoint). Finally, theportion of each node's redo log that needs to be scanned during recoveryis always shorter because the redo log for every node does not need tobe scanned from the earliest unwritten change in the entire system.

Further, prior persistent storage write protocols, in the presence of aglobal cache, assume access to a synchronized global clock, where valuesfrom the clock are used as log sequence numbers (LSNs). The techniquespresented herein do not need access to a synchronized global clock.Further, prior techniques require a global master (GLM) that maintainslock coherency and the recovery sequence numbers of the dirty data itemsin the cluster. In addition, prior techniques cannot be easily extendedto systems where the master is distributed across several nodes (DLM).

Hardware Overview

FIG. 9 is a data item diagram that illustrates a computer system 900upon which an embodiment of the invention may be implemented. Computersystem 900 includes a bus 902 or other communication mechanism forcommunicating information, and a processor 904 coupled with bus 902 forprocessing information. Computer system 900 also includes a main memory906, such as a random access memory (RAM) or other dynamic storagedevice, coupled to bus 902 for storing information and instructions tobe executed by processor 904. Main memory 906 also may be used forstoring temporary variables or other intermediate information duringexecution of instructions to be executed by processor 904. Computersystem 900 further includes a read only memory (ROM) 908 or other staticstorage device coupled to bus 902 for storing static information andinstructions for processor 904. A storage device 910, such as a magneticpersistent storage or optical persistent storage, is provided andcoupled to bus 902 for storing information and instructions.

Computer system 900 may be coupled via bus 902 to a display 912, such asa cathode ray tube (CRT), for displaying information to a computer user.An input device 914, including alphanumeric and other keys, is coupledto bus 902 for communicating information and command selections toprocessor 904. Another type of user input device is cursor control 916,such as a mouse, a trackball, or cursor direction keys for communicatingdirection information and command selections to processor 904 and forcontrolling cursor movement on display 912. This input device typicallyhas two degrees of freedom in two axes, a first axis (e.g., x) and asecond axis (e.g., y), that allows the device to specify positions in aplane.

The invention is related to the use of computer system 900 forimplementing the techniques described herein. According to oneembodiment of the invention, those techniques are performed by computersystem 900 in response to processor 904 executing one or more sequencesof one or more instructions contained in main memory 906. Suchinstructions may be read into main memory 906 from anothercomputer-readable medium, such as storage device 910. Execution of thesequences of instructions contained in main memory 906 causes processor904 to perform the process steps described herein. In alternativeembodiments, hard-wired circuitry may be used in place of or incombination with software instructions to implement the invention. Thus,embodiments of the invention are not limited to any specific combinationof hardware circuitry and software.

The term “computer-readable medium” as used herein refers to any mediumthat participates in providing instructions to processor 904 forexecution. Such a medium may take many forms, including but not limitedto, non-volatile media, volatile media, and transmission media.Non-volatile media includes, for example, optical or magnetic persistentstorages, such as storage device 910. Volatile media includes dynamicmemory, such as main memory 906. Transmission media includes coaxialcables, copper wire and fiber optics, including the wires that comprisebus 902. Transmission media can also take the form of acoustic or lightwaves, such as those generated during radio-wave and infra-red datacommunications.

Common forms of computer-readable media include, for example, a floppydisk, a flexible disk, hard disk, magnetic tape, or any other magneticmedium, a CD-ROM, any other optical medium, punchcards, papertape, anyother physical medium with patterns of holes, a RAM, a PROM, and EPROM,a FLASH-EPROM, any other memory chip or cartridge, a carrier wave asdescribed hereinafter, or any other medium from which a computer canread.

Various forms of computer readable media may be involved in carrying oneor more sequences of one or more instructions to processor 904 forexecution. For example, the instructions may initially be carried on amagnetic disk of a remote computer. The remote computer can load theinstructions into its dynamic memory and send the instructions over atelephone line using a modem. A modem local to computer system 900 canreceive the data on the telephone line and use an infra-red transmitterto convert the data to an infra-red signal. An infra-red detector canreceive the data carried in the infra-red signal and appropriatecircuitry can place the data on bus 902. Bus 902 carries the data tomain memory 906, from which processor 904 retrieves and executes theinstructions. The instructions received by main memory 906 mayoptionally be stored on storage device 910 either before or afterexecution by processor 904.

Computer system 900 also includes a communication interface 918 coupledto bus 902. Communication interface 918 provides a two-way datacommunication coupling to a network link 920 that is connected to alocal network 922. For example, communication interface 918 may be anintegrated services digital network (ISDN) card or a modem to provide adata communication connection to a corresponding type of telephone line.As another example, communication interface 918 may be a local areanetwork (LAN) card to provide a data communication connection to acompatible LAN. Wireless links may also be implemented. In any suchimplementation, communication interface 918 sends and receiveselectrical, electromagnetic or optical signals that carry digital datastreams representing various types of information.

Network link 920 typically provides data communication through one ormore networks to other data devices. For example, network link 920 mayprovide a connection through local network 922 to a host computer 924 orto data equipment operated by an Internet Service Provider (ISP) 926.ISP 926 in turn provides data communication services through the worldwide packet data communication network now commonly referred to as the“Internet” 928. Local network 922 and Internet 928 both use electrical,electromagnetic or optical signals that carry digital data streams. Thesignals through the various networks and the signals on network link 920and through communication interface 918, which carry the digital data toand from computer system 900, are exemplary forms of carrier wavestransporting the information.

Computer system 900 can send messages and receive data, includingprogram code, through the network(s), network link 920 and communicationinterface 918. In the Internet example, a server 930 might transmit arequested code for an application program through Internet 928, ISP 926,local network 922 and communication interface 918.

The received code may be executed by processor 904 as it is received,and/or stored in storage device 910, or other non-volatile storage forlater execution. In this manner, computer system 900 may obtainapplication code in the form of a carrier wave.

In the foregoing specification, the invention has been described withreference to specific embodiments thereof. It will, however, be evidentthat various modifications and changes may be made thereto withoutdeparting from the broader spirit and scope of the invention. Thespecification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense.

1. A method for writing data items to persistent storage, the methodcomprising the steps of: maintaining, within a first node, a first queueof entries that correspond to dirty data items that need to be writtento persistent storage; maintaining, within the first node, a secondqueue of entries that correspond to dirty data items that need to bewritten to persistent storage; in response to determining that a dirtydata item, corresponding to a particular entry, needs to be transferredto a node other than said first node, moving said particular entry fromsaid first queue to said second queue; selecting, at the first node,which data items to write to persistent storage based on which queue, ofthe first queue and the second queue, an entry for a data item residesin, wherein said selecting gives priority to data items that correspondto entries in said second queue; and writing, to persistent storage, aparticular data item selected based on which queue, of the first queueand the second queue, an entry for the particular data item resides in.2. The method of claim 1 wherein the step of moving entries includesmoving an entry from said first queue to said second queue in responseto a message received by said first node, wherein said message indicatesthat another node has requested the data item that corresponds to saidentry.
 3. A method for writing data items to persistent storage, themethod comprising the steps of: maintaining a forced-write count foreach of said data items; incrementing the forced-write count of a dataitem whenever the data item is written to persistent storage by one nodefor transfer of the data item to another node; selecting which dirtydata items to write to persistent storage based on the write countsassociated with the data items; and writing one or more selected dirtydata items, which were selected based on the write counts associatedwith the selected dirty data items, to persistent storage.
 4. The methodof claim 3 further comprising the steps of: storing dirty data itemsthat have forced-write counts above a certain threshold in a particularqueue; and when selecting dirty data items to write to persistentstorage, giving priority to data items stored in said particular queue.5. A computer-readable medium carrying instructions for writing dataitems to persistent storage, the instructions, which when executed byone or more processors, causes: maintaining, within a first node, afirst queue of entries that correspond to dirty data items that need tobe written to persistent storage; maintaining, within the first node, asecond queue of entries that correspond to dirty data items that need tobe written to persistent storage; in response to determining that adirty data item, corresponding to a particular entry, needs to betransferred to a node other than said first node, moving said particularentry from said first queue to said second queue; selecting, at thefirst node, which data items to write to persistent storage based onwhich queue, of the first queue and the second queue, an entry for adata item resides in, wherein said selecting gives priority to dataitems that correspond to entries in said second queue; and writing, topersistent storage, a particular data item selected based on whichqueue, of the first queue and the second queue, an entry for theparticular data item resides in.
 6. The computer-readable medium ofclaim 5 wherein the step of moving entries includes moving an entry fromsaid first queue to said second queue in response to a message receivedby said first node, wherein said message indicates that another node hasrequested the data item that corresponds to said entry.
 7. Acomputer-readable medium carrying instructions for writing data items topersistent storage, the instructions, which when executed by one or moreprocessors, causes: maintaining a forced-write count for each of saiddata items; incrementing the forced-write count of a data item wheneverthe data item is written to persistent storage by one node for transferof the data item to another node; selecting which dirty data items towrite to persistent storage based on the write counts associated withthe data items; and writing one or more selected dirty data items, whichwere selected based on the write counts associated with the selecteddirty data items, to persistent storage.
 8. The computer-readable mediumof claim 7 further comprising instructions for performing the steps of:storing dirty data items that have forced-write counts above a certainthreshold in a particular queue; and when selecting dirty data items towrite to persistent storage, giving priority to data items stored insaid particular queue.